About the Book :-
Focusing on a data-centric perspective, this book provides a comprehensive overview of data mining on almost all aspects, including its basic concepts, current technologies, popular techniques, commercial products, and future challenges.
Three parts divide Data Mining :
Part I describes technologies for data mining – database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining
Part II presents tools and techniques – getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information
Part III examines emerging trends – mining distributed and heterogeneous data sources; multimedia data, such as text, images, video; mining data on the World Wide Web; metadata aspects of mining; and privacy issues.
This self-contained book also contains two appendices providing exceptional information on technologies, such as data management, and artificial intelligence.
Is there a need for mining? Do you have the right tools? Do you have the people to do the work? Do you have sufficient funds allocated to the project? All these questions must be answered before embarking on a project. Data Mining provides singular guidance on appropriate applications for specific techniques as well as thoroughly assesses valuable product information.
Contents :-
Preface
About the Author
Chapter 1. Introduction
Part I. Technologies for Data Mining
Chapter 2. Database Systems
Chapter 3. Data Warehousing
Chapter 4. Some Other Technologies for Data Mining
Chapter 5. Architecural Support for Data Mining
Part II. Techniques and Tools for Data Mining
Chapter 6. The Process of Data Mining
Chapter 7. Data Mining Outcomes, Approaches, and Techniques
Chapter 8. Logic Programming as a Data Mining Technique
Chapter 9. Data Mining Tools
Part III. Trends in Data Mining
Chapter 10. Mining Distributed, Heterogeneous, and Legacy Databases
Chapter 11. Multimedia Data Mining
Chapter 12. Data Mining and the World Wide Web
Chapter 13. Security and Privacy Issues for Data Mining
Chapter 14. Metadata Aspects of Mining
Chapter 15. Summary and Directions
References
Appendices
Index.
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